Search Results (19)

Electronic medical records (EMRs) are fundamental to clinical decision support systems (CDSS). Conventional EMR structures still fail to capture the cyclical nature of treatment plans, leading to fragmented data representation and reduced decision accuracy. This study addresses this gap by proposing a cycle-based EMR framework that systematically integrates treatment cycles, enabling structured, sequential data organization. Treatment cycles categorize patient data into iterative phases, reflecting disease progression and repeated interventions, ensuring data continuity and analytical precision. A dataset inspired by MIMIC-III was developed to empirically evaluate this approach, incorporating treatment cycle fields to enhance data continuity and analytical precision. The results indicate that cycle-based structuring preserves critical variations in patient responses, improves treatment outcome predictions, and strengthens CDSS recommendations. While this approach offers substantial benefits, challenges such as workflow adaptation, usability, and interoperability must be addressed to facilitate seamless integration into clinical practice. Despite these challenges, this study establishes a scientifically validated foundation for cycle-based EMRs, aligning data structures with real-world clinical workflows. By rectifying data organization, this approach elevates diagnostic accuracy, optimizes treatment planning, and enhances patient outcomes, contributing to the future of precision medicine. Full article

Clinical Decision Support Systems (CDSSs) have become indispensable in medical decision-making. The heterogeneity and vast volume of medical data require firm attention to data management and integration strategies. On the other hand, CDSS functionality must be enhanced through improved human–computer interaction (HCI) principles. This study investigates the bidirectional relationship between data management practices (specifically data entry management, data transformation, and data integration) and HCI principles within CDSSs. Through a novel framework and practical case studies, we demonstrate how high-quality data entry, driven by controlled workflows and automated technologies, is crucial for system usability and reliability. We explore the transformative positive impact of robust data management techniques, including standardization, normalization, and advanced integration solutions, on the HCI elements and overall system performance. Conversely, we illustrate how effective HCI design improves data quality by reducing cognitive load, minimizing errors, and fostering user engagement. The findings reveal a synergistic relationship between HCI and data science, providing actionable insights for designing intuitive and efficient CDSSs. This research bridges the gap between technical and human-centric approaches, advancing CDSS usability, decision accuracy, and clinician trust for better patient outcomes. Full article

Automated driving (AD) is a new technology that aims to mitigate traffic accidents and enhance driving efficiency. This study presents a deep reinforcement learning (DRL) method for autonomous vehicles that can safely and efficiently handle highway overtaking scenarios. The first step is to create a highway traffic environment where the agent can be guided safely through surrounding vehicles. A hierarchical control framework is then provided to manage high-level driving decisions and low-level control commands, such as speed and acceleration. Next, a special DRL-based method called deep deterministic policy gradient (DDPG) is used to derive decision strategies for use on the highway. The performance of the DDPG algorithm is compared with that of the DQN and PPO algorithms, and the results are evaluated. The simulation results show that the DDPG algorithm can effectively and safely handle highway traffic tasks. Full article

Automated driving is a promising development in reducing driving accidents and improving the efficiency of driving. This study focuses on developing a decision-making strategy for autonomous vehicles, specifically addressing maneuvers such as lane change, double lane change, and lane keeping on highways, using deep reinforcement learning (DRL). To achieve this, a highway driving environment in the commercial multi-body simulation software IPG Carmaker 11 version is established, wherein the ego vehicle navigates through surrounding vehicles safely and efficiently. A hierarchical control framework is introduced to manage these vehicles, with upper-level control handling driving decisions. The DDPG (deep deterministic policy gradient) algorithm, a specific DRL method, is employed to formulate the highway decision-making strategy, simulated in MATLAB software. Also, the computational procedures of both DDPG and deep Q-network algorithms are outlined and compared. A set of simulation tests is carried out to evaluate the effectiveness of the suggested decision-making policy. The research underscores the advantages of the proposed framework concerning its convergence rate and control performance. The results demonstrate that the DDPG-based overtaking strategy enables efficient and safe completion of highway driving tasks. Full article

Due to the high pollution of the transportation sector, nowadays the role of electric vehicles has been noticed more and more by governments, organizations, and environmentally friendly people. On the other hand, the problem of electric vehicle routing (EVRP) has been widely studied in recent years. This paper deals with an extended version of EVRP, in which electric vehicles (EVs) deliver goods to customers. The limited battery capacity of EVs causes their operational domains to be less than those of gasoline vehicles. For this purpose, several charging stations are considered in this study for EVs. In addition, depending on the operational domain, a full charge may not be needed, which reduces the operation time. Therefore, partial recharging is also taken into account in the present research. This problem is formulated as a multi-objective integer linear programming model, whose objective functions include economic, environmental, and social aspects. Then, the preemptive fuzzy goal programming method (PFGP) is exploited as an exact method to solve small-sized problems. Also, two hybrid meta-heuristic algorithms inspired by nature, including MOSA, MOGWO, MOPSO, and NSGAII_TLBO, are utilized to solve large-sized problems. The results obtained from solving the numerous test problems demonstrate that the hybrid meta-heuristic algorithm can provide efficient solutions in terms of quality and non-dominated solutions in all test problems. In addition, the performance of the algorithms was compared in terms of four indexes: time, MID, MOCV, and HV. Moreover, statistical analysis is performed to investigate whether there is a significant difference between the performance of the algorithms. The results indicate that the MOSA algorithm performs better in terms of the time index. On the other hand, the NSGA-II-TLBO algorithm outperforms in terms of the MID, MOCV, and HV indexes. Full article

In this research, the pure fatigue behaviors of AM60 magnesium alloy with polylactic acid (PLA) coating (PF-AM60-PLA) and the corrosion fatigue behaviors of magnesium alloy with PLA coating (CF-AM60-PLA) were evaluated. Polymer coating was made by fused deposition modeling (FDM) with a 3D printer and attached to standard fatigue test specimens with glue. Then, after 27 days of immersion in the simulated body fluid (SBF), the high-cycle bending fatigue test was performed on samples. Due to corrosion, the weight of the specimens was reduced by an average of 35%. The corrosion rate decreased in the first 7 days and then increased. PF samples with a coating had an average 49% increase in fatigue lifetime. Regarding the CF samples, despite the use of a 10-times stronger solution, the fatigue lifetime of these samples decreased by only 35%. The field-emission scanning electron microscopy (FESEM) results also showed cleavage plates and striations. In addition, the separation of the glue from the coating and Mg was observed. Corrosion products, in addition to microcracks and holes, were seen on the fracture surface of CF specimens, which caused the stress concentration and the crack initiation. Holes caused by the release of gases were also observed in polymer coatings, which were fabricated by 3D printing. Full article

The Persian Qanats, ancient underground aqueduct systems that have provided irrigation water to arid regions in Iran for over 3000 years, are recognized as a vital element of the country’s cultural heritage. Eleven of these impressive structures have been included on the UNESCO World Heritage List, underlining their cultural, social, political, and physical significance. As these underground heritage sites offer a unique opportunity for fostering territorial collaboration and social capital between tourists and the local community, it is important to develop a comprehensive model to influence the behavior of tourists, officials, and natives in their treatment of these invaluable sites. This study aimed to design a sustainable behavior model for underground heritage tourism management in Persian Qanats that have been listed as UNESCO World Heritage properties. The research employed a theme analysis approach, utilizing a statistical sample of 22 base managers and Qanat tourism experts. The study used content and thematic analysis to develop a research model that guarantees the sustainable protection of these valuable underground heritage sites by shaping the behavior of tourists, officials, and natives. The proposed model serves as a guideline for effective behavior management, leading to the preservation of these significant underground heritage sites for future generations. In conclusion, this study provides valuable insights into the sustainable management of Persian Qanats and the promotion of a strong sense of territorial collaboration and social capital between tourists and the local community. Full article

Global environmental governance (GEG) is one of the world’s major attempts to address climate change issues through mitigation and adaptation strategies. Despite a significant improvement in GEG’s structural, human, and financial capital, the global commons are decaying at an unprecedented pace. Among the global commons, land has the largest share in GEG. Land use change, which is rooted in increasing populations and urbanization, has a significant role in greenhouse gas (GHG) emissions. As a response, land governance and, consequently, good land governance, have arisen as normative concepts emerging from a series of success factors (notably economic development, environmental conservation, and social justice) to achieve greater sustainability. However, global land governance has shown little success in helping GEG due to the lack of intellectual and flexible thinking over governing the land sector. Consequently, reforming land governance “in a smart way” is one of the most critical actions that could contribute to achieving GEG goals. Hence, we propose a smart land governance (SLG) system that will be well addressed, understood, and modeled in a systemic and dynamic way. A smart system may be smart enough to adapt to different contexts and intellectual responses in a timely fashion. Accordingly, SLG is able to promote shared growth and solve many land sector problems by considering all principles of good land governance. Therefore, in order to enhance adaptive land governance systems, efficient land administration and management are required. This study’s outcomes will raise the comprehension of the problems of land management, providing an excellent framework to help land planners and policy-makers, as well as the development of strategic principles with respect to the principal multidimensional components of SLG. Full article

Nowadays, according to the intention of many hospitals and medical centers to computerize their processes and medical treatments, including data forms and medical images, which are generating a considerable amount of data, IT specialists and data scientists who are oriented to eHealth and related issues know the importance of data integration and its benefits. This study indicates the significance of data integration, especially in medical information systems. It means that the medical subsystems in the HIS (hospital information system) must be integrated, and it is also necessary to unify with the MIS (management information system). In this paper, the accuracy level of the extracted reports from the information system (to evaluate the staff’s performance) will be measured in two ways: (1) At first, the performance of the clinic reception staff will be evaluated. In this way, the personnel attendance system is an independent and separate software, and the mentioned evaluation has been performed by its report. (2) The following year, in the same location, the same evaluation has been performed based on the data extracted from the personnel attendance subsystem, which has been added to the medical information system as an integrated information system. After comparing the accuracy level of both ways, this paper concludes that when the personnel attendance subsystem as a part of the MIS has been unified with the HIS, the reports and, consequently, management decisions will be more accurate; therefore, the managers and decision-makers will perceive the importance of data integration more than in the past. Full article

The hydrangea (Hydrangea macrophylla (Thunb). Ser.), an ornamental plant, has good marketing potential and is known for its capacity to change the colour of its inflorescence depending on the pH of the cultivation media. The molecular mechanisms causing these changes are still uncertain. In the present study, transcriptome and targeted metabolic profiling were used to identify molecular changes in the RNAome of hydrangea plants cultured at two different pH levels. De novo assembly yielded 186,477 unigenes. Transcriptomic datasets provided a comprehensive and systemic overview of the dynamic networks of the gene expression underlying flower colour formation in hydrangeas. Weighted analyses of gene co-expression network identified candidate genes and hub genes from the modules linked closely to the hyper accumulation of Al³⁺ during different stages of flower development. F3′5′H, ANS, FLS, CHS, UA3GT, CHI, DFR, and F3H were enhanced significantly in the modules. In addition, MYB, bHLH, PAL6, PAL9, and WD40 were identified as hub genes. Thus, a hypothesis elucidating the colour change in the flowers of Al³⁺-treated plants was established. This study identified many potential key regulators of flower pigmentation, providing novel insights into the molecular networks in hydrangea flowers. Full article

The presented article provides a comprehensive study on the stability analysis of earth-fill dams under rapid drawdown and transient flow conditions used to prepare stability analysis charts by conducting coupled finite-element numerical and analytical limit equilibrium procedures. In this regard, the impacts of different rapid drawdown conditions on the safety factor of the Alavian earth-fill dam are determined. The slope stability charts present for both shallow and deep slip surfaces with various permeabilities are verified by ground information obtained with extensive instrumentation on the dam’s site. The results showed that by decreasing the permeability of the core’s material, despite preventing seepage, the instability risk of the upstream slope as a result of rapid drawdown intensifies. Also, as stability charts can be stated, with increasing the slip surface’s depth and decreasing the hydraulic hydration, the reliability decreases, and the sliding surfaces’ sensitivity increases based on the drawdown rates, which have been revealed to be from 0.2 to 0.6, the most critical state for safety factors, showing significant declines. Full article

The Gavkhouni wetland provides many environmental and economic benefits for the central region of Iran. In recent decades, it has completely dried up several times with substantial impacts on local ecosystems and climate. Remote sensing-based Land Surface Temperature (LST), Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI) in combination with in-situ data were used to investigate the trend of the Gavkhouni wetland dryness and the associated impact on the variability of local air temperature. The results indicate that the wetland has increasingly experienced drier conditions since the year 2000. The wetland was almost completely dry in 2009, 2011, 2015 and 2017. In addition, the results show that Gavkhouni wetland dryness has a significant impact on local climate, increasing the mean seasonal air temperature by ~1.6 °C and ~1 °C in spring and summer, respectively. Overall, this study shows that remote sensing imagery is a valuable source for monitoring dryness and air temperature variations in the region. Moreover, the results provide a basis for effective water allocation decisions to maintain the hydrological and ecological functionality of the Gavkhouni wetland. Considering that many factors such as latitude, cloud cover, and the direction of prevailing winds affect land surface and air temperatures, it is suggested to use a numerical climate model to improve a regional understanding of the effects of wetland dryness on the surrounding climate. Full article

In this paper, a lowpass filter is designed using half elliptical resonators with a wide stopband. New formulas are presented to achieve a circuit model for the half elliptical resonators used in this work. Additionally, the transfer function and transmission zero equations are used to adjust the frequency of the transmission zeros of the filter. The cut-off frequency of the lowpass filter is 1.26 GHz with a sufficiently large stopband, extending from 1.48 GHz to 20 GHz. The proposed filter’s figure of merit is 62,520, demonstrating its outperformance compared to the state of the art. The filter is implemented on a RT-5880 substrate with a constant dielectric of 2.2, thickness of 31 mil and loss tangent of 0.0009. The LPF was fabricated and tested, showing good agreement between the simulated and measured results. Full article

This study estimates the effect of interest-free agriculture credit on the market participation and urban-rural linkages of rice growers in Pakistan. A survey was conducted to collect primary data using purposive and simple random sampling techniques from Punjab, Pakistan. This study applied the Instrument Variable (IV) approach and Ordinary Least Square (OLS) to evaluate the impact of interest-free credit on market participation and income. The results show a mixed influence of interest-free credit on rice growers’ market participation and urban-rural linkages. In general, the effect is negative when farmers obtained credit for six months. However, it shows a positive impact when farmers’ received credit for the next consecutive crop. Our findings suggest that the provision of interest-free credit for one year served a better purpose as it significantly attempted to alleviate budget constraints and endorsed farmers to increase land size under rice cultivation and improve productivity, market participation, and urban-rural linkages. The study provides three valid instruments and, therefore, a superior estimate of effect is achieved which can be leveraged to better support coherent agri-food policymaking. Full article

Agriculture is an irrefutable part of food policy. This paper aims to introduce an integrated method using MICMAC and AHP techniques to deal with understanding the key strategic variables of agricultural system. MICMAC was used to determine the classifications of variables and AHP was applied to weigh these classifications. MICMAC is a structural analysis tool used to structure ideas and AHP is an effective tool to deal with complex decision making and helps decision-makers making the best decision. The results show that strategic variables had different types of influence and direct, indirect, and potential dependencies did not have the same importance. AHP-MICMAC not only considers these differences, but also puts a total priority weight for each variable. These characteristics have an important role in forming strategies and scenarios for agricultural development. Therefore, the case of Iran was used to illustrate the application of MICMAC aiming to supply instructions for the development of agriculture system. Full article